Document Databases

Elasticsearch

Elasticsearch is a distributed search and analytics engine created by Elastic, built on Apache Lucene. It distinguishes itself from traditional databases by offering near real-time full-text search capabilities with inverted indices and relevance scoring. Companies like Netflix, Uber, and GitHub use it for log analytics, product search, and monitoring workloads. A key technical detail is its use of JSON over HTTP for all operations, including queries via the Query DSL. It operates as a cluster of nodes with automatic sharding and replication for scalability.

Also known as: elastic, es

🧊Why learn Elasticsearch?

Use Elasticsearch when you need fast, scalable full-text search or log analysis, such as for e-commerce product catalogs or application monitoring dashboards. It is not the right pick for transactional workloads requiring ACID compliance, like financial record-keeping, due to its eventual consistency model. The Elastic community acknowledges a weakness in handling complex joins and relationships, which are better suited to relational databases. This trade-off prioritizes search performance over data integrity in distributed scenarios.

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Alternatives to Elasticsearch

Algolia Meilisearch

Other Document Databases

Academic Databases

Academic databases are specialized digital repositories that store and provide access to scholarly literature, research papers, theses, dissertations, and other academic publications. They are designed to support research and education by offering structured, searchable collections of peer-reviewed content, often with advanced indexing and citation features. These databases are essential tools for researchers, students, and institutions to discover and retrieve credible academic information.

Always On Availability Groups

Always On Availability Groups is a high-availability and disaster recovery solution in Microsoft SQL Server that provides database-level failover for groups of databases. It allows multiple copies of a set of databases (availability replicas) to be maintained across different servers, ensuring data redundancy and automatic failover in case of primary server failure. This feature supports both synchronous and asynchronous data replication modes to balance performance and data protection needs.

Amazon Aurora is a fully managed, MySQL and PostgreSQL-compatible relational database service built for the cloud. It combines the performance and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases, offering up to five times the throughput of standard MySQL and three times that of PostgreSQL. Aurora automatically handles tasks like hardware provisioning, database setup, patching, backups, and replication, while providing high durability and availability through distributed, fault-tolerant, self-healing storage.

Amazon Aurora is a fully managed relational database service compatible with MySQL and PostgreSQL, offered as part of Amazon Web Services (AWS). It provides high performance, scalability, and availability by using a distributed, fault-tolerant storage system that automatically replicates data across multiple Availability Zones. Aurora is designed to deliver up to five times the throughput of standard MySQL and three times that of PostgreSQL while maintaining compatibility with existing applications.

Amazon Aurora Provisioned

Amazon Aurora Provisioned is a fully managed relational database service from AWS that offers high performance, scalability, and availability with MySQL and PostgreSQL compatibility. It uses a distributed, fault-tolerant storage system that automatically scales up to 128 TB per database instance, providing fast read replicas and continuous backup to Amazon S3. This provisioned model requires users to pre-allocate and pay for database instance capacity, making it suitable for predictable workloads.

Amazon Aurora Serverless

Amazon Aurora Serverless is an on-demand, auto-scaling configuration for Amazon Aurora, a MySQL and PostgreSQL-compatible relational database built for the cloud. It automatically starts up, shuts down, and scales capacity up or down based on application demand, eliminating the need to manage database instances. This serverless model is designed for applications with intermittent, unpredictable, or variable workloads.